Social networking or social network services are today used for the building of online communities through the usage of web-based applications which have recently shown to be quite successful in terms of a steadily increasing number of users. However, one major issue concerning social networking is the matter of privacy, as users are often reluctant to reveal personal information on the Internet when it is felt that the privacy controls are not sufficiently strong or flexible or when there is a perception that the user is not in control of their own personal data. This reluctance tends to become stronger when the personal information contains information about a user's physical condition or location. Pseudonymity (a fictitious and often anonymous identity) is commonly used on the Internet to provide privacy controls but is challenging in a social network service setting where typically a user wishes to know the real-world identity of a person he or she is communicating with.
The personal information people often are reactant to share with remote or un-known persons include, for example, a so called social network profile in the form of a list of descriptive information about the user, social connections that describe a persons relations with other users, information about membership in Internet forums, communities and groups etc.
Examples of social networks that facilitate communication between persons include Facebook, Orkut, LinkedIn, Plaxo, Cyworld, Mixi, QQ and MySpace. Each of these applications applies various models for handling personal/private information, such as i) the “open model”, where all members of the social network can see all information about a user, ii) the “friend model”, where all friends of a user can see all personal information about a user, while non-friends see restricted amounts of information, and iii) the “granular model”, where certain friends can see certain information about a user at that user's discretion, while “non-friends” see restricted amounts of information. In this context the granular model can be seen as an improved version of the friend model in terms of allowing a user to define what information shall be revealed to other persons, which often is implemented by allowing a user to provide each friend with a particular set of information access rights, while non-friends by default can only see restricted or no information. Privacy control is often implemented by using access control to prevent unauthorized people gaining access to the data. Encryption to protect data in transit is also used and sometimes the amount of available personal data is minimized.
The level of desired privacy is often a matter of trust which tends to be implemented as a rather static setting in the social networking service, as indicated by the above described models for handling personal information. By increasing trust the level of anonymity in the social networking service may be decreased, thus making more personal information available to more trusted users. Moreover, for establishing trust (making more information available) it is also relevant to allow a person to meet the “right person” in the social network, i.e. a person whom one shares common interests and values.
An example of a known technique that relates to increasing trust and thus at least indirectly reduce the need of anonymity is described in US-2003/0004782 A1, where an apparatus automates the process of determining whether individuals in social groups have positive or negative responses to each other, and automates the process of notifying the people involved of such responses. The apparatus receives inputs from participants who have engaged in a group social event indicating the positive and negative responses they have toward each other. Next, searches are done for mutual positive responses and for other patterns of response that provide valuable feedback to the participants, such as which participant received the most positive responses overall. The system then reveals this information to the participants and allows the participants who matched with each other to communicate privately.
Another example of a technique for matching people with mutual interest is disclosed in US-2008/0052288 A1, where a system uses a mutual commit process for automatically matching people. The process includes a recommender system that generates people recommendations based on inferences of preferences derived from system usage behaviors. The process also includes variations of a mutual commitment process that may only reveal a first person's interest in making their expression of interest with a second person if a reciprocal interest in revealing expression of interest is indicated. By doing so, potential embarrassment and fear of rejection can be reduced, i.e. the risk of identifying the “wrong person” is reduced by the system.
Though the technologies described above may assist in investigating whether two users are matching, and thereby potentially increase trust between the users and accordingly reduce the need of anonymity, they are limited to rather static matches where users either “match” or “do not match”.